Visual tracking

Augmented Memory for Correlation Filters in Real-Time UAV Tracking

The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements. Previous appearances are also gradually forgotten due to the exponential decay of historical views in traditional …

Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio Optimization

Current unmanned aerial vehicle (UAV) visual tracking algorithms are primarily limited with respect to":" (i) the kind of size variation they can deal with, (ii) the implementation speed which hardly meet the real-time requirement. In this work, a …

DR^2Track: Towards Real-Time Visual Tracking for UAV via Distractor Repressed Dynamic Regression

Visual tracking has yielded promising applications with unmanned aerial vehicle (UAV). In literature, the advanced discriminative correlation filter (DCF) type trackers generally distinguish the foreground from the background with a learned regressor …

Learning Consistency Pursued Correlation Filters for Real-Time UAV Tracking

Correlation filter (CF) has proven its superb efficiency in visual tracking for unmanned aerial vehicle (UAV) applications. To enhance the temporal smoothness of the filter, many CF-based approaches introduce temporal regularization terms to penalize …

Towards Robust Visual Tracking for Unmanned Aerial Vehicle with Tri-Attentional Correlation Filters

Object tracking has been broadly applied in unmanned aerial vehicle (UAV) tasks in recent years. However, existing algorithms still face difficulties such as partial occlusion, clutter background, and other challenging visual factors. Inspired by the …

Object Saliency-Aware Dual Regularized Correlation Filter for Real-Time Aerial Tracking

Spatial regularization has proven itself to be an effective method in terms of alleviating the boundary effect and boosting the performance of a discriminative correlation filter (DCF) in aerial visual object tracking. However, existing spatial …

Intermittent Contextual Learning for Keyfilter-Aware UAV Object Tracking Using Deep Convolutional Feature

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter corruption. Several methods enlarging the search area can mitigate …

BiCF: Learning Bidirectional Incongruity-Aware Correlation Filter for Efficient UAV Object Tracking

Correlation filters (CFs) have shown excellent performance in unmanned aerial vehicle (UAV) tracking scenarios due to their high computational efficiency. During the UAV tracking process, viewpoint variations are usually accompanied by changes in the …

Training-Set Distillation for Real-Time UAV Object Tracking

Correlation filter (CF) has recently exhibited promising performance in visual object tracking for unmanned aerial vehicle (UAV). Such online learning method heavily depends on the quality of the training-set, yet complicated aerial scenarios like …

Keyfilter-Aware Real-Time UAV Object Tracking

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter corruption. Several methods enlarging the search area can mitigate …